Health literacy and breast cancer preventive practices among market women in Oshodi Local Government Area of Lagos State, Nigeria
Bibliographic record
Abstract
Background: Health literacy connotes understanding health-related issues and applying a clear understanding of implications in making decisions about one's healthcare needs. Early detection and prompt treatment are cornerstone strategies of breast cancer control. This study assessed the relationship between health literacy and breast cancer prevention practices. Methods: This study was conducted in Lagos State. Participants' socio-demographic characteristics, knowledge about breast cancer, attitude towards breast cancer and practice of screening methods available were obtained. Health literacy was assessed with the health literacy domain of a validated questionnaire (Cronbach's alpha of 0.75) validated by test-retest reliability) that evaluated the ability to use a language to understand health instructions, cognitive awareness of basic health-related situations, symptom recognitions and health actions required. Health literacy variables were measured on a 19-point rating scale. Results: Most participants(40%) were between the ages of 31 and 40, while women aged 60 years and above constituted the least proportion (3.1%) of the sample. The mean health literacy score was 12.27 (SD+1.5). A significant proportion(78.4%) of the women had heard of breast cancer. Participants with university/HND education are less likely (OR = 0.431; 95%CI = 0.039,0.759) to have low health literacy. Also, participants with higher income were less likely to have low health literacy, and knowledge of breast cancer risk factors was generally low. Conclusion: This study shows an above-average mean health literacy score amongst these women; however, inadequate knowledge of risk factors still exists. Education level and income are significant in increasing health literacy on breast cancer preventive practices amongst market women in Lagos, Nigeria.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".